Agentic AI News – 12 February 2026
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Industry Adoption and Strategic Investment
Transforming Insurance: From Pilot Programs to Scalable Efficiency
The insurance sector is uniquely positioned to leverage agentic AI due to its deep data reserves and analytical workforce. While interest is high, many insurers struggle to move beyond pilot programs because of legacy infrastructure and fragmented data. Agentic AI offers a “resolve, not route” approach, automating complex workflows from first notice of loss to final billing. Successful implementations have already demonstrated significant gains, such as a 30% increase in claims processing efficiency and a 65% reduction in customer complaints. To achieve these results, leaders must move past organizational resistance by establishing AI Centers of Excellence and prioritizing high-volume, repeatable tasks that allow for iterative refinement and scalable growth.
Original Article: AI News
The Emerging Healthcare Divide: Scaling Investment for Structural Change
A new Deloitte report highlights a growing “AI divide” in healthcare, where 85% of leaders plan to increase agentic AI investments over the next three years. Early adopters are moving decisively toward enterprise-wide deployment, expecting cost savings of over 20%. In contrast, “watchers” remain cautious, often limited by smaller budgets and modest expectations. Agentic AI is evolving from a passive data repository into an active participant in care delivery, capable of orchestrating multi-step tasks like prior authorizations and clinical documentation. By automating administrative burdens, these intelligent agents allow clinicians to focus more on direct patient care, potentially reducing medical errors and flagging health risks earlier than traditional systems.
Original Article: Becker’s Hospital Review
The Outsourcing Dilemma: Enterprises Race for Speed Over Control
Research from SOUTHWORKS reveals that while interest in agentic AI has moved from experimentation to execution, most enterprises lack the internal capacity to scale these systems independently. Consequently, over 70% of organizations plan to source their AI capabilities through external platforms or consulting partners. This reliance on third-party vendors prioritizes speed-to-value but creates a potential “maturity gap” regarding long-term ownership and governance. Fragmented deployments remain common, with only 30% of surveyed firms having standardized enterprise-wide frameworks. The study warns that without clear internal ownership, the initial speed gained by outsourcing could lead to significant friction and security challenges as these autonomous systems become more embedded in core operations.
Original Article: Accesswire
E-Commerce and Telecommunications Innovations
Google’s Native AI Shopping: Seamless Purchases Within Gemini
Google is asserting its dominance in conversational commerce by integrating items from major retailers like Etsy and Wayfair directly into its agentic AI search results. Through the new “Universal Commerce Protocol,” shoppers can discover, evaluate, and purchase products without ever leaving the AI Mode or Gemini interface. This convergence of search and checkout marks a significant shift in the customer journey, moving away from traditional redirects to merchant websites. For retailers, this means product data must now be “agent-readable” to remain visible. Google’s pilot programs also include “Direct Offers,” allowing advertisers to surface exclusive, intent-based discounts within AI conversations, effectively turning AI assistants into personalized, real-time virtual sales associates.
Original Article: Retail Brew
Monetizing the Network: Telefónica and Nokia’s Push for Agentic APIs
Telefónica and Nokia have partnered to trial advanced AI protocols intended to accelerate the adoption of Network APIs. By testing Agent-to-Agent (A2A) and Model Context Protocol (MCP) standards, the companies aim to simplify how developers access and coordinate complex network services. Their initial focus involves a banking fraud prevention agent that uses real-time network data, such as SIM swap detection, to enhance security. This collaboration highlights a strategic shift toward a “fully agentic monetization ecosystem,” where AI agents autonomously orchestrate workflows across programmable networks. By lowering integration barriers for partners, the initiative paves the way for a new generation of telco-powered services that can be scaled and monetized more efficiently.
Original Article: TelcoTitans
Infrastructure, Security, and Leadership
Building Enterprise-Grade Agents with Oracle and Infosys
Infosys is utilizing Oracle Integration’s Model Context Protocol (MCP) tools to help enterprises move from conceptual AI demos to production-ready systems. This collaboration addresses the need for predictability, observability, and governance in agentic AI. By leveraging MCP, Infosys can reliably connect specialized AI agents with any enterprise application, breaking down data silos and automating complex business processes like global collections and invoicing. Oracle’s strategy focuses on embedding these “digital workers” directly into existing ERP and supply chain workflows. This approach ensures that AI actions are not just autonomous but also auditable and secure, providing the structural foundation necessary for mission-critical operations in manufacturing, finance, and logistics.
Original Article: Oracle Blog
Securing the Agentic Frontier: Overmind’s Intelligence-Led Approach
Overmind, a startup founded by former MI5 engineers, recently secured £2 million to address the unique security risks of agentic AI. Unlike traditional security tools, Overmind focuses on the operational integrity and safety of autonomous systems that can take actions in the real world. As AI agents gain the ability to manipulate data and execute transactions, the potential for catastrophic error or malicious exploitation grows. The team’s background in national security informs their approach to creating “safe rooms” and governance layers for AI. By focusing on the “control plane” of agentic behavior, Overmind provides enterprises with the visibility needed to ensure that autonomous agents remain within predefined ethical and operational boundaries.
Original Article: Tech Funding News
Leadership in the Agentic Age: Shifting from Manager to Strategist
Harvard Business School exploration of leadership in an agentic world suggests that AI agents will function as an “executive support team,” transforming the daily work of leaders. These agents act as competitive intelligence analysts, synthesizing vast amounts of data into actionable insights, and as digital “chiefs of staff” that align calendars with strategic priorities. However, the rise of agentic AI requires leaders to move beyond managing tasks to managing outcomes. Success in this new environment depends on a leader’s ability to define clear objectives and maintain human oversight over autonomous processes. Rather than replacing judgment, agentic AI frees leaders from administrative minutiae, allowing them to focus on high-value strategic thinking and organizational culture.
Original Article: HBS Working Knowledge
Defining the Agent: Why the Control Plane Is the True Product
This editorial argues that the true value of agentic AI does not lie in the “agent” itself, but in the “control plane”—the framework that governs and bounds its autonomy. While creating an autonomous system is relatively simple, ensuring that it operates safely within a complex environment is the real challenge. The article posits that the industry is currently obsessed with “agency,” yet fails to address “decision legitimacy” and accountability. Without a robust control plane, agents are merely unpredictable actors in a world that requires consistency. For executives, the focus must shift from buying individual agents to building an operating model where responsibility catches up with capability, ensuring that every autonomous decision is visible, justified, and controlled.
Original Article: Unhyped AI (Substack)
